Data

Multi-ancestry maternal GWAS summary statistics from "Multi-ancestry, trans-generational GWAS meta-analysis of gestational diabetes and glycaemic traits during pregnancy reveals limited evidence of pregnancy-specific genetic effects"

The University of Queensland
Dr Gunn-Helen Moen (Aggregated by) Dr Gunn-Helen Moen (Aggregated by) Professor David Evans (Aggregated by) Professor David Evans (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.48610/0aa6ba4&rft.title=Multi-ancestry maternal GWAS summary statistics from Multi-ancestry, trans-generational GWAS meta-analysis of gestational diabetes and glycaemic traits during pregnancy reveals limited evidence of pregnancy-specific genetic effects&rft.identifier=RDM ID: c10e8290-00b4-4065-bbde-a85cb61825b9&rft.publisher=The University of Queensland&rft.description=Maternal henotypes analysed: 1-hour glucose post-OGTT (1h_Glucose), 2-hour glucose post-OGTT (2h_Glucose), fasting glucose (FG), gestational diabetes mellitus (GDM), and glycated haemoglobin (HbA1c). Quality control prior to the meta-analysis excluded SNVs with poor imputation quality (r² < 0.3 or info < 0.4), minor allele count < 10, and/or effect allele frequency < 0.1%; genetic data were lifted over to GRCh38 where required. Multi-ancestry maternal meta-analyses used MR-MEGA including three principal components; summary statistics are provided for all populations combined (FG n = 55,371; 1hG n = 38,439; 2hG n = 46,401; HbA1c n = 9,724; GDM n = 814,450 [38,305 cases]), filtered at MAF ≥ 0.01 with SNPs removed if absent from ≥ 50% of the sample. For further details on sample sizes, analytical pipelines, and cohort-specific QC procedures, see Supplementary Materials.&rft.creator=Dr Gunn-Helen Moen&rft.creator=Dr Gunn-Helen Moen&rft.creator=Professor David Evans&rft.creator=Professor David Evans&rft.date=2025&rft_rights= https://guides.library.uq.edu.au/deposit-your-data/license-reuse-data-agreement&rft_subject=eng&rft_subject=Genomics and transcriptomics&rft_subject=Bioinformatics and computational biology&rft_subject=BIOLOGICAL SCIENCES&rft_subject=Statistical and quantitative genetics&rft_subject=Genomics&rft_subject=Genetics&rft_subject=Endocrinology&rft_subject=Clinical sciences&rft_subject=BIOMEDICAL AND CLINICAL SCIENCES&rft_subject=Obstetrics and gynaecology&rft_subject=Reproductive medicine&rft.type=dataset&rft.language=English Access the data
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[email protected]
Institute for Molecular Bioscience

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Maternal henotypes analysed: 1-hour glucose post-OGTT (1h_Glucose), 2-hour glucose post-OGTT (2h_Glucose), fasting glucose (FG), gestational diabetes mellitus (GDM), and glycated haemoglobin (HbA1c). Quality control prior to the meta-analysis excluded SNVs with poor imputation quality (r² < 0.3 or info < 0.4), minor allele count < 10, and/or effect allele frequency < 0.1%; genetic data were lifted over to GRCh38 where required. Multi-ancestry maternal meta-analyses used MR-MEGA including three principal components; summary statistics are provided for all populations combined (FG n = 55,371; 1hG n = 38,439; 2hG n = 46,401; HbA1c n = 9,724; GDM n = 814,450 [38,305 cases]), filtered at MAF ≥ 0.01 with SNPs removed if absent from ≥ 50% of the sample. For further details on sample sizes, analytical pipelines, and cohort-specific QC procedures, see Supplementary Materials.

Issued: 2025

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Biological Sciences | Biomedical and Clinical Sciences | Bioinformatics and Computational Biology | Clinical Sciences | Endocrinology | Genetics | Genomics | Genomics and Transcriptomics | Obstetrics and Gynaecology | Reproductive Medicine | Statistical and Quantitative Genetics | eng |

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local : UQ:289097

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